Histórico Veicular Nacional

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the annotations (idempotentHint=true), the description adds behavioral detail: it can establish a permanent non-expiring connection via config, or a session-only login via token, and no-args returns a link. This gives useful context about modes and state.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, information-dense paragraph. It is reasonably concise and front-loaded with the purpose, but could benefit from bullet points for clarity. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has no output schema, and the description only specifies the output for the no-args case ('to get the link'). It does not describe what happens after a successful token-based login, or potential errors, leaving some ambiguity for the agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage for the 'token' parameter, but the description fully explains it: an optional JWT pasted by the user, with one behavior when provided and another when omitted. This compensates completely for the schema gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: authenticating IDE agents via browser login and access token. It distinguishes itself from sibling tools like 'connect' by focusing on token exchange and session management.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides clear context for when to use the tool (IDE agents) and explains two usage modes: permanent config header or session-only token. However, it does not explicitly mention when not to use it or point to alternative tools, so it lacks explicit exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the baseline for transparency is lower. The description adds valuable context about state-dependent return values (authenticated:true vs. connect_url), which goes beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences with no filler. The core purpose is stated first ('Returns connection status and URLs'), and the additional behavior is explained concisely.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter read-only status tool, the description fully explains the return values in both success and failure scenarios. No output schema exists, but the description covers what the agent needs to know.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Since the tool has zero parameters, the description has no obligation to explain parameters. The baseline of 4 applies here because no parameter documentation is needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool as returning connection status and URLs, with a specific verb ('Returns') and resource. It also distinguishes itself from siblings like 'authenticate' by focusing on status rather than performing authentication.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context on what the tool does and its behavior under different conditions (all providers connected vs. missing credentials). However, it does not explicitly mention when to avoid using it or point to alternative tools, so it lacks explicit exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description goes well beyond the annotations. It discloses that invoke works even when the MCP is not installed, runs one-off without bloating the tool list, returns connect/checkout links for missing credentials/payment, and requires workspace owner/admin for writes. It also explains the installed_in_toolkit vs installed_in_workspace distinction. This is rich behavioral context that annotations do not provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but information-dense with no fluff—every sentence adds value explaining the dual catalog/execution role, edge cases, and auth. It is a single paragraph, which makes it harder to scan, but the size is justified given the tool's complexity (14 actions, 23 parameters).

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool this complex with no output schema, the description covers the main flow, auth requirements, payment/credential edge cases, and the prompt library feature. Missing details on some niche parameters, but overall it gives an agent a strong, actionable mental model.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It does explain the central parameters: action (via the enumerated actions and core flow), mcp_id, tool_id, and arguments. However, many parameters like limit, immediate, tier_slug, prompt_title, prompt_category, and prompt_targets are not explicitly described, leaving the agent to infer from names. It partially compensates but not fully for 23 parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a clear, specific statement: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It then details the core search/describe/invoke flow and distinguishes from sibling tools by naming report_bug, request_mcp, and prompt-related actions. This gives the tool a definite scope and role.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says when to use invoke vs install: 'Use install only to make an MCP PERMANENT in the active toolkit...; prefer invoke for a single/occasional use.' It also outlines when to use search, describe, invoke, and the prompt library functions. This is exemplary 'when-to vs alternatives' guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already provide safety hints (readOnlyHint=false, destructiveHint=false, idempotentHint=true). The description adds one useful behavioral detail by instructing to include the conversation array for reproduction, which hints at how the tool processes reports. However, it does not disclose potential side effects or response outcomes, and the annotations themselves are somewhat contradictory in spirit with a report tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences that front-load the purpose and then provide parameter guidance. No wasted words, well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple, and the description covers the main purpose and one parameter. However, given the lack of schema descriptions and output schema, it would benefit from explaining the other parameters and what happens after submission. It is adequate but not thorough.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description must compensate for parameter documentation. It only explains the 'conversation' parameter purpose; 'message' and 'context' are left undocumented in both schema and description. This is a clear gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb 'Report' with a clear resource ('a bug, missing feature, or send feedback'), making the tool's purpose immediately apparent. It also distinguishes itself from unrelated siblings by focusing on user feedback/reporting.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly states the context for using the tool (reporting bugs, missing features, or feedback) without needing to exclude alternatives since sibling tools are unrelated. It provides a clear 'when to use' but no explicit 'when not to use', so it stops short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds that it shows both platform and adapter versions, but does not disclose any additional behavioral aspects such as output format or potential latency, which is fine given the trivial nature.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence with no unnecessary words. It is front-loaded and immediately communicates the tool's function.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple version retrieval tool, the description is sufficiently complete. It names the exact outputs (platform and adapter versions) and, with the annotations covering safety and idempotence, covers the key context. No output schema exists, but the description itself answers the main question.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and the schema reflects this with no properties. The baseline for zero parameters is 4, and the description adds no param information because none is needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool shows current MCP platform and adapter versions, using a specific verb and resource. However, it does not explicitly distinguish itself from the sibling 'toolkit_info' tool, leaving some ambiguity about when to prefer this over that.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. There is no mention of context, exclusions, or related tools, so the agent receives no usage direction beyond the basic action.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds the specific components of the returned state (MCPs, connection status, accounts, catalog tool counts), which is useful context, but it does not describe the return format or any potential delays/errors. This matches the calibration example where added scoping detail earned a 3.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, front-loaded with the verb and resource, and enumerates the returned elements without unnecessary words. Every piece of information is relevant and directly supports tool selection.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (zero parameters, read-only, no output schema), the description fully captures its function and output categories. There is no missing information that would hinder an agent's decision to invoke it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has zero properties, so there are no parameters to explain. Per the rubric, a baseline of 4 applies for 0-parameter tools; the description needs no parameter compensation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses 'Returns' as a specific verb and clearly identifies the resource ('current toolkit state'), enumerating the exact contents: installed MCPs, connection status, accounts, and catalog tool counts. This distinguishes it from sibling tools like authenticate or connect, which describe actions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly implies when to use the tool: whenever one needs the current toolkit state, including MCP connections and accounts. It does not explicitly name alternatives or exclusions, but given the specificity of the output, the usage context is unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds meaningful behavioral context: no credentials required, prepaid credit model, public access legal basis, and LGPD controller responsibility. This goes beyond annotations and clarifies important operational and legal traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is organized into four sentences, each delivering useful information: purpose, hosting/payment, public status, and legal responsibility. It is slightly dense but not bloated; every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so the description should hint at the return content; it does not. Parameter requirements are ambiguous, and the 'completo' field is unexplained. However, the description covers access, payment, and legal context adequately for a read-only consultation tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It mentions 'CPF ou CNPJ' but the schema requires both Cpf and Cnpj as separate required fields, creating ambiguity about whether one or both must be provided. The 'completo' parameter is never explained. No formats, exclusivity, or usage semantics are given.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Histórico dos veículos vinculados a um CPF ou CNPJ em âmbito nacional' which is a specific verb+resource+scope. It clearly identifies the tool's function and differentiates it from unrelated sibling tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear usage context: hosted on the platform, no credentials needed, pay per query with prepaid credit, and that it accesses public official data. It doesn't explicitly name alternatives or exclusions, but the context is sufficient given no similar sibling tools exist.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.